In this section, we investigate the effect of popularity bias on different user groups (i.e., Niche, Diverse, and Bestseller-focused) in book recommendations. To this end, we use delta Group Average Popularity (\(\Delta \) GAP) metric proposed by Abdollahpouri et al. [1]} to evaluate the unfairness of popularity bias. We further use MAE, Precision, Recall, and NDCG to evaluate the performance of recommender algorithms. For each recommendation algorithm and user group, \(\Delta \) GAP measures the difference between the average popularity of the recommended books and the average expected popularity shown in the user's profiles history as follows:
\(\Delta GAP=\frac{GAP(g)_r-GAP(g)_p}{GAP(g)_p}\) 
